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Do you have any additional comments or suggestions regarding SAS documentation in general that will help us better serve you? This content is presented in an iframe, which your browser does not support. At the foundation of SAP IQ lies a column store technology that allows for speed compression and ad-hoc analysis. SAP IQ has an open interface approach towards its ecosystem. SAP IQ is also integrated with SAP’s Business Intelligence portfolio of products to form an end-to-end business analytics software stack, and is an integral component of SAP’s In-Memory Data Fabric Architecture and Data Management Platform. In the early 1990s, Waltham, Massachusetts-based Expressway Technologies, Inc.
Sybase acquired Expressway and re-introduced the product in 1995 as IQ Accelerator, then renamed it shortly thereafter to Sybase IQ, giving it version number 11. Sybase became one of the first mainstream companies to acknowledge the need for specialized products for the data warehouse market. Version 16 brings a re-engineered column store for extreme, petabyte scale, data volumes, and more extreme data compression. The development and testing of the 12. Intel Petascale lab in Santa Clara, Calif.
The actual release title SP03 is a follow-on to SP02, covering all platforms not affected by the release. SAP’s new approach streamlines and simplifies Data Warehousing into an In-Memory Data Fabric. SAP IQ has coupled with SAP HANA to deliver a distributed in-memory analytics platform. SAP HANA which acts as an operational data store for immediate analysis. When SAP IQ is used as an EDW, it can also be augmented with HANA’s in-memory technology.
Common uses include planning and analysis reports where simultaneous OLTP processing is needed. In this case, data flows from SAP IQ to SAP HANA. Column-orientation has a number of advantages. If a search is being done for items matching a particular value in a column of data, only the storage objects corresponding to that data column within the table need to be accessed.
A traditional row-based database would have to read the whole table, top to bottom. Another advantage is that when indexed correctly, a value that would have to be stored once in each row of data in a traditional database is stored only once, and in SAP IQ, an n-bitindex is used to access the data. Nbit and tiered indexing is used to allow for increased compression and fast, incremental batch loads. Additionally, the column-based storage enables SAP IQ to compress data efficiently on the fly. Prior to SAP IQ 16, each data page was structured as an array of cells of a fixed size, so all values have the same data type.
While this storage approach is efficient for structured and fixed length data, this does not hold for the more unstructured and variable sized data that is seen today. Bitmaps are used for secondary indexes. The benefit of shared-everything is that it’s more flexible in terms of the variety of queries that can be optimized—especially for balancing the needs of many concurrent users. However, the aforementioned storage architecture of SAP IQ allows compute and storage layers to scale out independently of each other and also allows these resources to be provisioned on-demand for better utilization without restructuring the underlying database.